I hope you bring that up as an example in favor on open-source, as an example that open-source works. In a closed-source situation it would either not be detected or reach the light of day.
In a closed source situation people using a pseudonym don't just randomly approach a company and say "hey can I help out with that?"
It was caught by sheer luck and chance, at the last minute - the project explicitly didn't have a bunch of eyeballs looking at it and providing a crowd-sourced verification of what it does.
I am all for open source - everything I produce through my company to make client work easier is open, and I've contributed to dozens of third party packages.
But let's not pretend that it's a magical wand which fixes all issues related to software development - open source means anyone could audit the code. Not that anyone necessarily does.
I was interested and looked at the actual patent: https://patents.justia.com/patent/4348422 (there seem to be multiple patent documents, but this one adds some explanation), and he writes "I have now surprisingly discovered".
https://tastydecafs.com/blogs/learn-about-decaf/co2-decaf further explains
"The story of C02 decaffeination goes back to 1967. It was then when a chemist at Max Planck Institute named Kurt Zosel stumbled upon an interesting discovery. Zosel, like many other chemists, was using high-pressure C02 to remove individual substances from other mixtures."
It must have something to do with caffeine being an alkaloid, while coffee overall is acidic. So I suspect that this pressurized CO2 is able to dominantly remove such alkaloids... I leave the details to a chemist :)
This is why I think that modeling elementary physics is nothing else than fitting data. We might end up with something that we perceive as "simple", or not. But in any case all the fitting has been hidden in the process of ruling out models. It's just that a lot of the fitting process is (implicitly) being done by theorists; we come up with new models and that are then being falsified.
For example, how many parameters does the Standard Model have? It's not clear what you count as a parameter. Do you count the group structure, the other mathematical structure that has been "fitted" through decades of comparisons with experiments?
You are using the word "fitting" rather loosely. We usually "fit" models of fixed function form and fixed number of parameters.
You are also glossing over centuries of precedent that predate high-energy physics, namely quantum field theory, special relativity, and foundational principles such as conservation of energy and momentum.
I find the article quite confusing and unclear to be honest. Are there any other sources?
This is the original NYT article from 2018 https://www.nytimes.com/2018/12/18/technology/facebook-priva...
"Internal documents show that the social network gave Microsoft, Amazon, Spotify and others far greater access to people’s data than it has disclosed."
Wait, seriously? Like 4-6 months ago? Like, yesterday in terms of how long they haven't had it? Sheesh, a day doesn't go by that I'm not reminded of how happy I am to have dropped FB so long ago.
Is academia supposed to compete? I think the researchers wish for that, but that's not directly how government funding agencies see it. From a government's funding perspective the goal is to train tomorrow's workforce. People learn in academia and then transition and contribute outside. As far as agencies like DOE go, that is an explicit goal.
Recently talked to a DOE program manager. I confronted them with the question why we do things like machine learning or quantum computing in academia, when there's no hope in matching industry for those things. His answer was that from an official perspective this isn't the goal, but future workforce training for national interests and security. NSF might differ slightly, but I think this makes sense.
Is knowing the presence of something more valuable than knowing the precise absence of something? In my opinion both drive our knowledge forward and challenge our current understanding and development of models.
